When a substance such as human tissue is subjected to a uniform magnetic field (polarizing field B0), the individual magnetic moments of the spins in the tissue attempt to align with this polarizing field, but process about it in random order at their characteristic Larmor frequency. If the substance, or tissue, is subjected to a magnetic field (excitation field B1) which is in the x-y plane and which is near the Larmor frequency, the net aligned moment, Mz, may be rotated, or “tipped”, into the x-y plane to produce a net transverse magnetic moment Mt. A signal is emitted by the excited spins after the excitation signal B1 is terminated, this signal may be received and processed to form an image.
When utilizing these signals to produce images, magnetic field gradients (Gx, Gy and Gz) are employed. Typically, the region to be imaged is scanned by a sequence of measurement cycles in which these gradients vary according to the particular localization method being used. The resulting set of received NMR signals are digitized and processed to reconstruct the image using one of many well known image reconstruction techniques.
Depending on the technique used, many NMR scans currently used to produce medical images require many minutes to acquire the necessary data. The reduction of this scan time is an important consideration, since reduced scan time increases patient throughput, improves patient comfort, and improves image quality by reducing motion artifacts. Many different strategies have been developed to shorten the scan time.
One such strategy is referred to generally as “parallel imaging.” Parallel imaging techniques use spatial information from arrays of RF receiver coils to compliment the encoding which would otherwise have to be obtained in a sequential fashion using RF pulses and field gradients (such as phase and frequency encoding). Each of the spatially independent receiver coils of the array carries certain spatial information in the form of a sensitivity profile. This information is utilized in order to achieve a complete location encoding by combining the simultaneously acquired coil data from the separate receiver coils. Specifically, parallel imaging techniques can reconstruct undersampled k-space whereby the number of phase-encoded lines acquired is reduced by increasing the distance between these lines while keeping the maximal extent covered in k-space fixed. The combination of the separate NMR signals produced by the separate receiver coils enables a reduction of the acquisition time required for an image (in comparison to conventional k-space data acquisition) by a factor which in the most favorable case equals the number of the receiver coils. Thus, the use of multiple receiver coils acts to increase imaging speed by accelerating the encoding, without increasing gradient switching rates or RF power.
Two categories of such parallel imaging techniques which have gained wide use with in vivo imaging are exemplified by the SENSitivity Encoding (SENSE) and generalized autocalibrating partially parallel acquisitions (GRAPPA) methods. With SENSE, the undersampled k-space data is first Fourier transformed into the image domain to produce an aliased image from each coil channel, and then the aliased images are, in one step, unaliased and combined by a linear transformation of the superimposed pixel values. This direct unaliasing performed by SENSE requires an explicit estimate of the receiver coil sensitivities.
In contrast, GRAPPA performs a reconstruction of the omitted k-space lines prior to Fourier transformation and coil combination, by constructing a weighted combination of neighboring lines acquired by the different receiver coils. In this way, the receiver coil sensitivities are only implicit in the image reconstruction process, and are not explicitly estimated.
GRAPPA belongs to a class of “auto-calibrated” techniques. With GRAPPA, calibration data in the form of k-space lines typically near the center of k-space are sampled at the Nyquist frequency. These Nyquist-sampled k-space lines are referred to as autocalibration signal (ACS) lines, which are used to determine weighting factors that are utilized to synthesize, or reconstruct, the missing k-space lines. In particular, a linear combination of individual coil data is used to create the missing lines of k-space. The coefficients for the combination are determined by fitting a subset of the calibration data (“source data”) to neighboring lines of the calibration data (“target data”) across all coil channels in order to learn the relationship between nearby lines of k-space data. These coefficients are later applied to estimating skipped k-space lines from neighboring acquired k-space lines in the accelerated reconstruction.
In dynamic MRI applications, such as functional imaging, interventional imaging, and cardiac imaging, there has long been a need in the art for systems and methods that provide higher spatial and temporal resolution and higher image quality. Accelerated parallel imaging methods are one mechanism to provide this.
One common rapid imaging method that benefits from accelerated parallel imaging is Echo Planar Imaging (EPI), which is a rapid acquisition technique that is broadly used in dynamic MRI applications, including functional, perfusion, and diffusion imaging in neuroimaging, body imaging, and cardiac imaging applications. In EPI, multiple lines of k-space are acquired after a single excitation and therefore it has the ability to freeze motion and to dynamically image the region of interest. However, EPI suffers however from multiple imaging artifacts, which limit its utility and its range of applications. These artifacts include: Nyquist ghosts, which arise from data mismatch that occurs from the rapid sampling of k-space; and geometric distortions, which arise from varying spin-phase evolutions in regions of magnetic field inhomogeneity, disrupting the Fourier encoding of the spin's location. Similar challenges with respect to Nyquist ghosts exist when using other pulse sequences, including turbo spin echo (TSE) and extensions of EPI, like 3D gradient and spin echo (GRASE) sequences. Parallel imaging has been previously combined with EPI and other pulse sequences, which favorably reduces the length of the readout to reduce geometric distortions. To date, many methods have been proposed to correct for Nyquist ghosts, but it remains challenging to completely eliminate their appearance in all applications.